Coaching portal and methods based on behavioral assessment data

ABSTRACT

An interface portal system that includes a non-transitory computer readable medium having a plurality of stored instructions adapted to generate a coaching portal based on behavioral assessment data, the plurality of instructions including instructions that, when executed, analyze one or more communications between a customer and an agent, wherein the analysis comprises instructions that, when executed, apply a linguistic-based psychological behavioral model to separated voice data for the customer, the agent, or both, from each communication by analyzing behavioral characteristics of the customer, the agent, or both, based on the one or more communications; instructions that, when executed, identify one or more customer-agent interaction events based on the analyzed behavioral characteristics; and instructions that, when executed, display a time-based graphic representation across a selected time interval based on one or more communications. Methods of providing coaching assessment based on behavioral assessment data are also included.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/230,032, filed Aug. 5, 2016, now allowed, which is a continuation ofU.S. patent application Ser. No. 14/960,194, filed Dec. 4, 2015, nowU.S. Pat. No. 9,432,511, which is a continuation of U.S. patentapplication Ser. No. 12/079,828, filed Mar. 28, 2008, now U.S. Pat. No.9,225,841, which claims priority to U.S. Provisional Patent ApplicationNo. 60/921,109, filed Mar. 30, 2007, and which is also acontinuation-in-part of U.S. patent application Ser. No. 11/365,432,filed Mar. 1, 2006, now U.S. Pat. No. 8,094,790, which is acontinuation-in-part of U.S. patent application Ser. No. 11/131,844,filed May 18, 2005, now abandoned, the disclosure of each of which ishereby incorporated herein by reference thereto.

TECHNICAL FIELD

The invention relates to a method and system for analyzing an electroniccommunication, more particularly, to analyzing a communication between acustomer and a contact center by applying a psychological behavioralmodel thereto to obtain behavioral assessment data and to calculate acustomer satisfaction score based on the assessment data.

BACKGROUND OF THE INVENTION

It is known to utilize telephone call centers to facilitate the receipt,response and routing of incoming telephone calls relating to customerservice, retention, and sales. Generally, a customer is in contact witha customer service representative (“CSR”) or call center agent who isresponsible for answering the customer's inquiries and/or directing thecustomer to the appropriate individual, department, information source,or service as required to satisfy the customer's needs.

It is also well known to monitor calls between a customer and a callcenter agent. Accordingly, call centers typically employ individualsresponsible for listening to the conversation between the customer andthe agent. Many companies have in-house call centers to respond tocustomers' complaints and inquiries. In many case, however, it has beenfound to be cost effective for a company to hire third party telephonecall centers to handle such inquiries. As such, the call centers may belocated thousands of miles away from the actual sought manufacturer orindividual. This often results in use of inconsistent and subjectivemethods of monitoring, training and evaluating call center agents. Thesemethods also may vary widely from call center to call center.

While monitoring such calls may occur in real time, it is often moreefficient and useful to record the call for later review. Informationgathered from the calls is typically used to monitor the performance ofthe call center agents to identify possible training needs. Based on thereview and analysis of the conversation, a monitor will make suggestionsor recommendations to improve the quality of the customer interaction.Improvements typically relate to an agent's performance, which generallyleads to higher customer satisfaction.

Accordingly, there is a need in customer relationship management (“CRM”)for an objective tool useful in improving the quality of customerinteractions with agents and ultimately customer relationships. Inparticular, a need exists for an objective monitoring and analysis toolwhich provides information about a customer's perception of aninteraction during a call. In the past, post-call data collectionmethods have been used to survey callers for feedback. This feedback maybe subsequently used by a supervisor or trainer to evaluate an agent.Although such surveys have enjoyed some degree of success, theirusefulness is directly tied to a customer's willingness to providepost-call data.

More “passive” methods have also been employed to collect data relatingto a customer's in-call experience. For example, U.S. Pat. No. 6,724,887to Eilbacher et al. is directed to a method and system for analyzing acustomer communication with a contact center. According to Eilbacher, acontact center may include a monitoring system which records customercommunications and a customer experience analyzing unit which reviewsthe customer communications. The customer experience analyzing unitidentifies at least one parameter of the customer communications andautomatically determines whether the identified parameter of thecustomer communications indicates a negative or unsatisfactoryexperience. According to Eilbacher, a stress analysis may be performedon audio telephone calls to determine a stress parameter by processingthe audio portions of the telephone calls. From this, it can then bedetermined whether the customer experience of the caller wassatisfactory or unsatisfactory.

While the method of Eilbacher provides some benefit with respect toreaching an ultimate conclusion as to whether a customer's experiencewas satisfactory or unsatisfactory, the method provides little insightinto the reasons for an experiential outcome. As such, the method ofEilbacher provides only limited value in training agents for futurecustomer communications. Accordingly, there exists a need for a systemthat analyzes the underlying behavioral characteristics of a customerand agent so that data relating to these behavioral characteristics canbe used for subsequent analysis and training.

Systems such as stress analysis systems, spectral analysis models andword-spotting models also exist for determining certain characteristicsof audible sounds associated with a communication. For example, systemssuch as those disclosed in U.S. Pat. No. 6,480,826 to Pertrushin providea system and method for determining emotions in a voice signal. However,like Eilbacher, these systems also provide only limited value intraining customer service agents for future customer interactions.Moreover, such methods have limited statistical accuracy in determiningstimuli for events occurring throughout an interaction.

It is well known that certain psychological behavioral models have beendeveloped as tools to evaluate and understand how and/or why one personor a group of people interacts with another person or group of people.The Process Communication Model™ (“PCM”) developed by Dr. Taibi Kahleris an example of one such behavioral model. Specifically, PCMpresupposes that all people fall primarily into one of six basicpersonality types: Reactor, Workaholic, Persister, Dreamer, Rebel andPromoter. Although each person is one of these six types, all peoplehave parts of all six types within them arranged like a “six-tierconfiguration.” Each of the six types learns differently, is motivateddifferently, communicates differently, and has a different sequence ofnegative behaviors in which they engage when they are in distress.Importantly each PCM personality type responds positively or negativelyto communications that include tones or messages commonly associatedwith another of the PCM personality types. Thus, an understanding of acommunicant's PCM personality type offers guidance as to an appropriateresponsive tone or message. There exists a need for a system and methodthat analyzes the underlying behavioral characteristics of a customerand agent communication by automatically applying a psychologicalbehavioral model such as, for example PCM, to the communication.

Devices and software for recording and logging calls to a call centerare well known. However, application of word-spotting analytical toolsto recorded audio communications can pose problems. Devices and softwarethat convert recorded or unrecorded audio signals to text files are alsoknown the art. But, translation of audio signals to text files oftenresults in lost voice data due to necessary conditioning and/orcompression of the audio signal. Accordingly, a need also exists toprovide a system that allows a contact center to capture audio signalsand telephony events with sufficient clarity to accurately apply alinguistic-based psychological behavioral analytic tool to a telephoniccommunication.

Moreover, it is generally known to store and/or record telephone callsfor later review. However, due to the high volume of recorded callswithin, for example, a call center, it is difficult to find meaningfulexamples of calls to drive improvements at a later time. Call centerstypically hire individuals to manually sift or sort through calls tofind good examples. Typically, an individual must typically manuallylisten to a call and manually rank or categorize the call.

A need exists, therefore, for a systematic way to automaticallycategorize and sort calls so as to search and find or otherwise navigateto call examples that may be utilized to drive improvements. Further, aneed exists for a method and system for inputting multiple metrics fordetermining call examples, and navigation to call examples based onthese metrics.

The present invention is provided to solve the problems discussed aboveand other problems, and to provide advantages and aspects not previouslyprovided. A full discussion of the features and advantages of thepresent invention is deferred to the following detailed description,which proceeds with reference to the accompanying drawings.

SUMMARY OF THE INVENTION

A first aspect of the disclosure encompasses an embodiment including aninterface portal system that includes a non-transitory computer readablemedium comprising a plurality of instructions stored therein adapted togenerate a coaching portal based on behavioral assessment data, theplurality of instructions including instructions that, when executed,analyze one or more communications between a customer and an agent,wherein the analysis includes instructions that, when executed, apply alinguistic-based psychological behavioral model to separated voice datafor the customer, the agent, or both, from each communication byanalyzing behavioral characteristics of the customer, the agent, orboth, based on the one or more communications, instructions that, whenexecuted, identify one or more customer-agent interaction events basedon the analyzed behavioral characteristics, and instructions that, whenexecuted, display a time-based graphic representation including aplurality of the identified customer-agent interaction events across aselected time interval based on one or more communications.

A second aspect of the disclosure encompasses an embodiment including amethod of providing coaching assessment based on behavioral assessmentdata across one or more recorded communications, which includesanalyzing, by a server, one or more communications between a customerand an agent, wherein the analysis comprises instructions that, whenexecuted, apply a linguistic-based psychological behavioral model toseparated voice data for the customer, the agent, or both, from eachcommunication by analyzing behavioral characteristics of the customer,the agent, or both, based on the one or more communications, identifyingone or more customer-agent interaction events based on the analyzedbehavioral characteristics, and displaying a time-based graphicrepresentation including a plurality of the identified customer-agentinteraction events across a selected time interval based on one or morecommunications.

In a third aspect of the disclosure, the disclosure encompasses anon-transitory computer readable medium including a plurality ofinstructions stored therein adapted to generate a customer satisfactionscore based on behavioral assessment data, the plurality of instructionsincluding instructions that, when executed, analyze one or morecommunications between a customer and an agent, wherein the analysisincludes instructions that, when executed, apply a linguistic-basedpsychological behavioral model to each communication to determine apersonality type of the customer by analyzing behavioral characteristicsof the customer based on the one or more communications; instructionsthat, when executed, select at least one filter criterion which includesa customer, an agent, a team, or a call type, instructions that, whenexecuted, calculate a customer satisfaction score using the at least oneselected filter criterion across a selected time interval and based onone or more communications, and instructions that, when executed,display a report including the calculated customer satisfaction score toa user that matches the at least one selected filter criterion for theselected time interval.

In a fourth aspect of the disclosure, the disclosure encompasses amethod of generating a customer satisfaction score based on behavioralassessment data across one or more recorded communications that includesby analyzing one or more communications between a customer and an agent,wherein the analyzing includes applying a linguistic-based psychologicalbehavioral model to each communication to determine a personality typeof the customer by analyzing behavioral characteristics of the customerbased on the one or more communications, selecting at least one filtercriterion which includes a customer, an agent, a team, or a call type,calculating a customer satisfaction score using the at least oneselected filter criterion across a selected time interval and based onone or more communications, and displaying a report including thecalculated customer satisfaction score to a user that matches the atleast one selected filter criterion for the selected time interval.

In a fifth aspect, the disclosure encompasses a system configured togenerate a customer satisfaction score based on behavioral assessmentdata across one or more recorded communications, which includes anon-transitory computer readable medium operably coupled to one or moreprocessors, the non-transitory computer readable medium including aplurality of instructions stored therein that are accessible to, andexecutable by, the one or more processors, wherein the plurality ofinstructions includes instructions that, when executed, analyze one ormore communications between a customer and an agent, wherein theanalysis includes instructions that, when executed, apply alinguistic-based psychological behavioral model to each communication todetermine a personality type of the customer by analyzing behavioralcharacteristics of the customer based on the one or more communications,instructions that, when executed, select at least one filter criterionwhich includes a customer, an agent, a team, or a call type,instructions that, when executed, calculate a customer satisfactionscore using the at least one selected filter criterion across a selectedtime interval and based on one or more communications, and instructionsthat, when executed, display a report including the calculated customersatisfaction score to a user that matches the at least one selectedfilter criterion for the selected time interval.

According to a further aspect of the present invention, a method foranalyzing a communication between a customer and a contact center isprovided. According to the method, a communication is separated into atleast first constituent voice data and second constituent voice data.One of the first and second constituent voice data is analyzed by miningthe voice data and applying a predetermined linguistic-basedpsychological behavioral model to one of the separated first and secondconstituent voice data. Behavioral assessment data is generated whichcorresponds to the analyzed voice data.

According to another aspect of the present invention, the communicationis received in digital format. The step of separating the communicationinto at least a first and second constituent voice data comprises thesteps of identifying a communication protocol associated with thecommunication, and recording the communication to a first electronicdata file. The first electronic data file is comprised of a first andsecond audio track. The first constituent voice data is automaticallyrecorded on the first audio track based on the identified communicationprotocol, and the second constituent voice data is automaticallyrecorded on the second audio track based on the identified communicationprotocol. At least one of the first and second constituent voice datarecorded on the corresponding first and second track is separated fromthe first electronic data file. It is also contemplated that two firstdata files can be created, wherein the first audio track is recorded toone of the first data file and the second audio track is recorded to theother first data file.

According to another aspect of the present invention, the methoddescribed above further comprises the step of generating a text filebefore the analyzing step. The text file includes a textual translationof either or both of the first and second constituent voice data. Theanalysis is then performed on the translated constituent voice data inthe text file.

According to another aspect of the present invention, the predeterminedlinguistic-based psychological behavioral model is adapted to assessdistress levels in a communication. Accordingly, the method furthercomprises the step of generating distress assessment data correspondingto the analyzed second constituent voice data.

According to yet another aspect of the present invention event data isgenerated. The event data corresponds to at least one identifyingindicia and time interval. The event data includes at least one ofbehavioral assessment data or distress assessment data. It is alsocontemplated that both behavioral assessment data and distressassessment data are included in the event data.

According to still another aspect of the present invention, thecommunication is one of a plurality of communications. Accordingly, themethod further comprises the step of categorizing the communication asone of a plurality of call types and/or customer categories. Thecommunication to be analyzed is selected from the plurality ofcommunications based upon the call type and/or the customer category inwhich the communication is categorized.

According to still another aspect of the present invention, a responsivecommunication to the communication is automatically generated based onthe event data generated as result of the analysis.

According to another aspect of the present invention, a computer programfor analyzing a communication is provided. The computer program isembodied on a computer readable storage medium adapted to control acomputer. The computer program comprises a plurality of code segmentsfor performing the analysis of the communication. In particular, a codesegment separates a communication into first constituent voice data andsecond constituent voice data. The computer program also has a codesegment that analyzes one of the first and second voice data by applyinga predetermined psychological behavioral model to one of the separatedfirst and second constituent voice data. And, a code segment is providedfor generating behavioral assessment data corresponding to the analyzedconstituent voice data.

According to yet another aspect of the present invention, the computerprogram comprises a code segment for receiving a communication indigital format. The communication is comprised of a first constituentvoice data and a second constituent voice data. A code segmentidentifies a communication protocol associated with the communication. Acode segment is provided for separating the first and second constituentvoice data one from the other by recording the communication in stereoformat to a first electronic data file. The first electronic data fileincludes a first and second audio track. The first constituent voicedata is automatically recorded on the first audio track based on theidentified communication protocol, and the second constituent voice datais automatically recorded on the second audio track based on theidentified communication protocol.

A code segment applies a non-linguistic based analytic tool to theseparated first constituent voice data and generates phone event datacorresponding to the analyzed first constituent voice data. A codesegment is provided for translating the first constituent voice datainto text format and storing the translated first voice data in a firsttext file. A code segment analyzes the first text file by mining thetext file and applying a predetermined linguistic-based psychologicalbehavioral model to the text file. Either or both of behavioralassessment data and distress assessment data corresponding to theanalyzed first voice data is generated therefrom.

According to another aspect of the present invention, the above analysisis performed on the second constituent voice data. Additionally, a codesegment is provided for generating call assessment data by comparativelyanalyzing the behavioral assessment data and distress assessment datacorresponding to the analyzed first voice data and the behavioralassessment data and distress assessment data corresponding to theanalyzed second voice data. The computer program has a code segment foroutputting event data which is comprised of call assessment datacorresponding to at least one identifying indicia and at least onepredetermined time interval.

According to still another aspect of the present invention, a method foranalyzing an electronic communication is provided. The method comprisesthe step of receiving an electronic communication in digital format. Theelectronic communication includes communication data. The communicationdata is analyzed by applying a predetermined linguistic-basedpsychological behavioral model thereto. Behavioral assessment datacorresponding to the analyzed communication data is generated therefrom.

The method described can be embodied in a computer program stored on acomputer readable media. The a computer program would include codesegments or routines to enable all of the functional aspects of theinterface described or shown herein.

According to another aspect of the invention, a computer program fortraining a customer service representative by analyzing a communicationbetween a customer and a contact center is provided. A code segmentselects at least one identifying criteria. A code segment identifies apre-recorded first communication corresponding to the selectedidentifying criteria. The first communication has first event dataassociated therewith. A code segment generates coaching assessment datacorresponding to the identified pre-recorded first communication. A codesegment identifies a pre-recorded second communication corresponding tothe selected identifying criteria. The second communication has secondevent data associated therewith. A code segment compares the identifiedpre-recorded second communication to the identified first communicationwithin the coaching assessment data. A code segment generates anotification based on the comparison of the identified pre-recordedsecond communication with the identified first communication within thecoaching assessment data.

According to yet another aspect of the present invention, a code segmentgenerates a first performance score for the coaching assessment. A codesegment generates a second performance score for the pre-recorded secondcommunication. The notification is generated based on a comparison offirst performance score with the second performance score.

According to still another aspect of the present invention, a codesegment identifies a plurality of pre-recorded first communicationsbased on at least one identifying criteria. Each of the firstcommunications has first event data associated therewith. A code segmentfor identifies a plurality of pre-recorded second communications basedon at least one identifying criteria. Each of the second communicationshaving second event data associated therewith. A code segment generatesa first performance score for each of the plurality of prerecorded firstcommunications and a code segment generates a second performance scorefor each of the plurality of prerecorded second communications. A codesegment generates a notification if a predetermined number of secondperformance scores are at least one of less than a predeterminedthreshold of the first performance scores and greater than apredetermined threshold of the first performance scores.

According to another aspect of the present invention, a computer programfor training a customer service representative by analyzing acommunication between a customer and a contact center is provided. Acode segment selects at least one identifying criteria. A code segmentidentifies a pre-recorded first communications corresponding to theselected identifying criteria. The first communication having firstevent data associated therewith. A code segment generates coachingassessment data corresponding to the identified pre-recorded firstcommunication. A code segment compares the identified firstcommunication within the coaching assessment data with a predeterminedidentifying criteria value threshold. A code segment generates anotification based on the comparison of the identified firstcommunication with the coaching assessment data with a predeterminedidentifying criteria value threshold.

According to yet another aspect of the invention, a code segmentgenerates a first performance score for the coaching assessment data. Acode segment generates a second performance for the identifying criteriavalue threshold. A code segment generates a notification. Thenotification is generated based on a comparison of first performancescore and the second performance score.

According to another aspect of the invention, a code segment identifiesa plurality of pre-recorded first communications based on at least oneidentifying criteria. Each of the first communications having firstevent data associated therewith. A code segment generates a firstperformance score for each of the plurality of prerecorded firstcommunications based on the at least one identifying criteria. A codesegment generates a second performance score based on the identifyingcriteria value threshold. A code segment generates a notification. Thenotification is generated if a predetermined threshold of firstperformance scores are at least one of less than the second performancescore and greater than the second performance scores.

According to still another aspect of the present invention, the computerprogram further comprises a code segment for generating a graphical userinterface (“GUI”). The GUI is adapted to display a first field forenabling identification of customer interaction event information on adisplay. The customer interaction event information includes callassessment data based on the psychological behavioral model applied tothe analyzed constituent voice data of each customer interaction event.The computer program also includes a code segment for receiving inputfrom a user for identifying at least a first customer interaction event.A code segment is also provided for displaying the customer interactionevent information for the first customer interaction event.

According to one aspect of the present invention, the GUI enables a userof the system to locate one or more caller interaction events (i.e.,calls between a caller and the call center), and to display informationrelating to the event. In particular, the graphical user interfaceprovides a visual field showing the results of the psychologicalbehavioral model that was applied to a separated voice data from thecaller interaction event. Moreover, the interface can include a link toan audio file of a selected caller interaction event, and a visualrepresentation that tracks the portion of the caller interaction that iscurrently heard as the audio file is being played.

According to one aspect of the invention, the graphical user interfaceis incorporated in a system for identifying one or more callerinteraction events and displaying a psychological behavioral modelapplied to a separated voice data of a customer interaction event. Thesystem comprises a computer coupled to a display and to a database ofcaller interaction event information. The caller interaction eventinformation includes data resulting from application of a psychologicalbehavioral model to a first voice data separated from an audio wave formof a caller interaction event. Additionally, the caller eventinformation can also include additional information concerning eachcall, such as statistical data relating to the caller interaction event(e.g., time, date and length of call, caller identification, agentidentification, hold times, transfers, etc.), and a recording of thecaller interaction event.

The system also includes a processor, either at the user's computer orat another computer, such as a central server available over a networkconnection, for generating a graphical user interface on the display.The graphical user interface comprises a selection visual field forenabling user input of caller interaction event parameters for selectionof at least a first caller interaction event and/or a plurality ofcaller interaction events. The caller interaction event parameters caninclude one or more caller interaction event identifying characteristic.These characteristics can include, for example, the caller's name orother identification information, a date range, the agent's name, thecall center identification, a supervisor identifier, etc. For example,the graphical user interface can enable a user to select all callerinteraction events for a particular caller; or all calls handled by aparticular agent. Both examples can be narrowed to cover a specifiedtime period or interval. The interface will display a selected callerinteraction event field which provides identification of callerinteraction events corresponding to the user input of caller interactionevent parameters.

The graphical user interface also includes a conversation visual fieldfor displaying a time-based representation of characteristics of thecaller interaction event(s) based on the psychological behavioral model.These characteristics were generated by the application of apsychological behavioral model to a first voice data separated from anaudio wave form of a caller interaction event which is stored as part ofthe caller interaction event information.

The conversation visual field can include a visual link to an audio fileof the caller interaction event(s). Additionally, it may also include agraphical representation of the progress of the first caller interactionevent that corresponds to a portion of the audio file being played. Forexample, the interface may show a line representing the call and amoving pointer marking the position on the line corresponding to theportion of the event being played. Additionally, the time-basedrepresentation of characteristics of the caller interaction event caninclude graphical or visual characteristic elements which are alsodisplayed in the conversation visual field. Moreover, the characteristicelements are located, or have pointers to, specific locations of thegraphical representation of the progress of the event corresponding towhere the element was generated by the analysis.

The graphical user interface further includes a call statistics visualfield selectable by a user for displaying statistics pertaining to thecaller interaction events. The statistics in the call statistics visualfield can include, for example: call duration, caller talk time, agenttalk time, a caller satisfaction score, an indication of the number ofsilences greater than a predetermined time period, and an agentsatisfaction score.

The graphical user interface can also include a number of other visualfields. For example, the graphical user interface can include a callersatisfaction report field for displaying one or more caller satisfactionreports, or a user note field for enabling a user of the system to placea note with the first caller interaction event.

In accordance with another embodiment of the invention, a method foridentifying one or more caller interaction events and displaying ananalysis of a psychological behavioral model applied to a separatedvoice data from the caller interaction event comprises providing agraphical user interface for displaying a first field for enablingidentification of caller interaction event information on a display, thecaller interaction event information including analysis data based on apsychological behavioral model applied to a first separated voice dataof each caller interaction event; receiving input from a user foridentifying at least a first caller interaction event; and, displayingthe caller interaction event information for the first callerinteraction event on the display. The step of receiving input from auser can include receiving at least one or more of a caller identifier,a call center identifier, an agent identifier, a supervisor identifier,and a date range.

The step of displaying the caller interaction event information for thefirst caller interaction event on the display can include displaying atime-based representation of characteristics of the first callerinteraction event based on the psychological behavioral model. Themethod can also include providing an audio file of the first callerinteraction event. In this regard, the displaying of the time-basedrepresentation of characteristics of the first caller event based on thepsychological behavioral model can include displaying a graphicalrepresentation of the progress of the first caller interaction eventthat corresponds to a portion of the audio file being played.

The graphical user interface can be generated by a user's localcomputer, or from a remote server coupled to the user's computer via anetwork connection. In this latter instance, the method can furtherinclude creating a web page containing the graphical user interface thatis downloadable to a user's computer, and downloading the page via thenetwork connection.

The method can include providing other visual fields for enabling otherfunctions of the system. For example, the method can include providing afield in the graphical user interface for enabling a user to place anote with the information for the first caller interaction event.

The graphical user interface described can be embodied in a computerprogram stored on a computer readable media. The a computer programwould include code segments or routines to enable all of the functionalaspects of the interface described or shown herein.

Other features and advantages of the invention will be apparent from thefollowing specification taken in conjunction with the followingdrawings.

BRIEF DESCRIPTION OF THE DRAWINGS

To understand the present invention, it will now be described by way ofexample, with reference to the accompanying drawings in which:

FIG. 1 is a block diagram of call center;

FIG. 2 is a block diagram of the recording engine and behavioralanalysis engine according to the present invention;

FIG. 3 is a block diagram of a computer used in connection with thepresent invention;

FIG. 4 is a flow chart illustrating the process of analyzing atelephonic communication in accordance with the present invention;

FIG. 5 is a flow chart illustrating the process of analyzing atelephonic communication in accordance with the present invention;

FIG. 6 is a flow chart illustrating the process of analyzing atelephonic communication in accordance with the present invention;

FIG. 7 is a block diagram of a telephonic communication system accordingto the present invention;

FIG. 8 is a block diagram of a telephonic communication system accordingto the present invention;

FIG. 9 is a block diagram of a telephonic communication system with amulti-port PSTN module according to the present invention;

FIG. 10 is a flow chart illustrating the process of recording andseparating a telephonic communication in accordance with the presentinvention;

FIG. 11 is a flow chart illustrating the process of recording andseparating a telephonic communication in accordance with the presentinvention;

FIG. 12 is a flow chart illustrating the process of analyzing separatedconstituent voice data of a telephonic communication in accordance withthe present invention;

FIG. 13 is a flow chart illustrating the process of analyzing separatedconstituent voice data of a telephonic communication in accordance withthe present invention;

FIG. 14-32 are graphical user interface screens of the resultant outputfrom the process of analyzing voice data of a telephonic communicationin accordance with the present invention;

FIG. 33 is a flow chart illustrating the process the training the callcenter agent by analyzing a telephonic communication; and, FIG. 34-36are graphical user interface screens of the resultant output from theprocess of analyzing voice data of a telephonic communication inaccordance with the present invention.

DETAILED DESCRIPTION

While this invention is susceptible of embodiments in many differentforms, there is shown in the drawings and will herein be described indetail preferred embodiments of the invention with the understandingthat the present disclosure is to be considered as an exemplification ofthe principles of the invention and is not intended to limit the broadaspect of the invention to the embodiments illustrated.

Referring to FIGS. 1-32, a method and system for analyzing an electroniccommunication between a customer and a contact center is provided. A“contact center” as used herein can include any facility or systemserver suitable for receiving and recording electronic communicationsfrom customers. Such communications can include, for example, telephonecalls, facsimile transmissions, e-mails, web interactions, voice over IP(“VoIP”) and video. It is contemplated that these communications may betransmitted by and through any type of telecommunication device and overany medium suitable for carrying data. For example, the communicationsmay be transmitted by or through telephone lines, cable or wirelesscommunications. As shown in FIG. 1, the contact center 10 of the presentinvention is adapted to receive and record varying electroniccommunications 11 and data formats that represent an interaction thatmay occur between a customer (or caller) 7 and a contact center agent 9during fulfillment of a customer/agent transaction.

As shown in FIG. 2, the present method and system for analyzing anelectronic communication between a customer 7 and a contact center 10comprises a recording engine 2 and an behavioral analysis engine 3. Aswill be described in further detail, an audio communication signal isrecorded, separated into constituent audio data, and analyzed inaccordance with the methods described below. It is contemplated that themethod for analyzing an electronic communication between a customer 7and a contact center 10 of the present invention can be implemented by acomputer program. Now is described in more specific terms, the computerhardware associated with operating the computer program that may be usedin connection with the present invention.

Process descriptions or blocks in figures should be understood asrepresenting modules, segments, or portions of code which include one ormore executable instructions for implementing specific logical functionsor steps in the process. Alternate implementations are included withinthe scope of the embodiments of the present invention in which functionsmay be executed out of order from that shown or discussed, includingsubstantially concurrently or in reverse order, depending on thefunctionality involved, as would be understood by those having ordinaryskill in the art.

FIG. 3 is a block diagram of a computer or server 12. For purposes ofunderstanding the hardware as described herein, the terms “computer” and“server” have identical meanings and are interchangeably used. Computer12 includes control system 14. The control system 14 of the inventioncan be implemented in software (e.g., firmware), hardware, or acombination thereof. In the currently contemplated best mode, thecontrol system 14 is implemented in software, as an executable program,and is executed by one or more special or general purpose digitalcomputer(s), such as a personal computer (PC; IBM-compatible,Apple-compatible, or otherwise), personal digital assistant,workstation, minicomputer, or mainframe computer. An example of ageneral purpose computer that can implement the control system 14 of thepresent invention is shown in FIG. 3. The control system 14 may residein, or have portions residing in, any computer such as, but not limitedto, a general purpose personal computer. Therefore, computer 12 of FIG.3 may be representative of any computer in which the control system 14resides or partially resides.

Generally, in terms of hardware architecture, as shown in FIG. 3, thecomputer 12 includes a processor 16, memory 18, and one or more inputand/or output (I/O) devices 20 (or peripherals) that are communicativelycoupled via a local interface 22. The local interface 22 can be, forexample, but not limited to, one or more buses or other wired orwireless connections, as is known in the art. The local interface 22 mayhave additional elements, which are omitted for simplicity, such ascontrollers, buffers (caches), drivers, repeaters, and receivers, toenable communications. Further, the local interface may include address,control, and/or data connections to enable appropriate communicationsamong the other computer components.

The processor 16 is a hardware device for executing software,particularly software stored in memory 18. The processor 16 can be anycustom made or commercially available processor, a central processingunit (CPU), an auxiliary processor among several processors associatedwith the computer 12, a semiconductor based microprocessor (in the formof a microchip or chip set), a macroprocessor, or generally any devicefor executing software instructions. Examples of suitable commerciallyavailable microprocessors are as follows: a PA-RISC seriesmicroprocessor from Hewlett-Packard Company, an 80.times.8 or Pentiumseries microprocessor from Intel Corporation, a PowerPC microprocessorfrom IBM, a Sparc microprocessor from Sun Microsystems, Inc., or a 8xxxseries microprocessor from Motorola Corporation.

The memory 18 can include any one or a combination of volatile memoryelements (e.g., random access memory (RAM, such as DRAM, SRAM, SDRAM,etc.)) and nonvolatile memory elements (e.g., ROM, hard drive, tape,CDROM, etc.). Moreover, memory 18 may incorporate electronic, magnetic,optical, and/or other types of storage media. The memory 18 can have adistributed architecture where various components are situated remotefrom one another, but can be accessed by the processor 16.

The software in memory 18 may include one or more separate programs,each of which comprises an ordered listing of executable instructionsfor implementing logical functions. In the example of FIG. 3, thesoftware in the memory 18 includes the control system 14 in accordancewith the present invention and a suitable operating system (O/S) 24. Anon-exhaustive list of examples of suitable commercially availableoperating systems 24 is as follows: (a) a Windows operating systemavailable from Microsoft Corporation; (b) a Netware operating systemavailable from Novell, Inc.; (c) a Macintosh operating system availablefrom Apple Computer, Inc.; (d) a UNIX operating system, which isavailable for purchase from many vendors, such as the Hewlett-PackardCompany, Sun Microsystems, Inc., and AT&T Corporation; (e) a LINUXoperating system, which is freeware that is readily available on theInternet; (f) a run time Vxworks operating system from WindRiverSystems, Inc.; or (g) an appliance-based operating system, such as thatimplemented in handheld computers or personal digital assistants (PDAs)(e.g., PalmOS available from Palm Computing, Inc., and Windows CEavailable from Microsoft Corporation). The operating system 24essentially controls the execution of other computer programs, such asthe control system 14, and provides scheduling, input-output control,file and data management, memory management, and communication controland related services.

The control system 14 may be a source program, executable program(object code), script, or any other entity comprising a set ofinstructions to be performed. When a source program, the program needsto be translated via a compiler, assembler, interpreter, or the like,which may or may not be included within the memory 18, so as to operateproperly in connection with the O/S 24. Furthermore, the control system14 can be written as (a) an object oriented programming language, whichhas classes of data and methods, or (b) a procedure programminglanguage, which has routines, subroutines, and/or functions, for examplebut not limited to, C, C++, Pascal, Basic, Fortran, Cobol, Perl, Java,and Ada. In one embodiment, the control system 14 is written in C++. TheI/O devices 20 may include input devices, for example but not limitedto, a keyboard, mouse, scanner, microphone, touch screens, interfacesfor various medical devices, bar code readers, stylus, laser readers,radio-frequency device readers, etc. Furthermore, the I/O devices 20 mayalso include output devices, for example but not limited to, a printer,bar code printers, displays, etc. Finally, the I/O devices 20 mayfurther include devices that communicate both inputs and outputs, forinstance but not limited to, a modulator/demodulator (modem; foraccessing another device, system, or network), a radio frequency (RF) orother transceiver, a telephonic interface, a bridge, a router, etc.

If the computer 12 is a PC, workstation, PDA, or the like, the softwarein the memory 18 may further include a basic input output system (BIOS)(not shown in FIG. 3). The BIOS is a set of software routines thatinitialize and test hardware at startup, start the O/S 24, and supportthe transfer of data among the hardware devices. The BIOS is stored inROM so that the BIOS can be executed when the computer 12 is activated.

When the computer 12 is in operation, the processor 16 is configured toexecute software stored within the memory 18, to communicate data to andfrom the memory 18, and to generally control operations of the computer12 pursuant to the software. The control system 14 and the O/S 24, inwhole or in part, but typically the latter, are read by the processor16, perhaps buffered within the processor 16, and then executed.

When the control system 14 is implemented in software, as is shown inFIG. 3, it should be noted that the control system 14 can be stored onany computer readable medium for use by or in connection with anycomputer related system or method. In the context of this document, a“computer-readable medium” can be any means that can store, communicate,propagate, or transport the program for use by or in connection with theinstruction execution system, apparatus, or device. The computerreadable medium can be for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, device, or propagation medium. More specific examples (anon-exhaustive list) of the computer-readable medium would include thefollowing: an electrical connection (electronic) having one or morewires, a portable computer diskette (magnetic), a random access memory(RAM) (electronic), a read-only memory (ROM) (electronic), an erasableprogrammable read-only memory (EPROM, EEPROM, or Flash memory)(electronic), an optical fiber (optical), and a portable compact discread-only memory (CDROM) (optical). The control system 14 can beembodied in any computer-readable medium for use by or in connectionwith an instruction execution system, apparatus, or device, such as acomputer-based system, processor-containing system, or other system thatcan fetch the instructions from the instruction execution system,apparatus, or device and execute the instructions.

In another embodiment, where the control system 14 is implemented inhardware, the control system 14 can be implemented with any or acombination of the following technologies, which are each well known inthe art: a discrete logic circuit(s) having logic gates for implementinglogic functions upon data signals, an application specific integratedcircuit (ASIC) having appropriate combinational logic gates, aprogrammable gate array(s) (PGA), a field programmable gate array(FPGA), etc.

FIG. 4 illustrates the general flow of one embodiment of the method ofanalyzing voice data according to the present invention. As shown, anuncompressed digital stereo audio waveform of a conversation between acustomer and a call center agent is recorded and separated into customervoice data and call center agent voice data 26. The voice dataassociated with the audio waveform is then mined and analyzed usingmulti-stage linguistic and non-linguistic analytic tools 28. Theanalysis data is stored 30 and can be accessed by a user 31 (e.g., CSRsupervisor) through an interface portal 32 for subsequent review 32. Thedigital stereo audio waveform is compressed 34 and stored 36 in an audiofile which is held on a media server 38 for subsequent access throughthe interface portal 32.

The method of the present invention is configured to postpone audiocompression until analysis of the audio data is complete. This delayallows the system to apply the analytic tools to a truer and clearerhi-fidelity signal. The system employed in connection with the presentinvention also minimizes audio distortion, increases fidelity,eliminates gain control and requires no additional filtering of thesignal.

As shown in FIG. 6, according to one embodiment, the method of thepresent invention more specifically comprises the step of separating atelephonic communication 2 into first constituent voice data and secondconstituent voice data 40. One of the first or second constituent voicedata is then separately analyzed by applying a predeterminedpsychological behavioral model thereto 42 to generate behavioralassessment data 44. In one embodiment discussed in detail below,linguistic-based behavioral models are adapted to assess behavior basedon behavioral signifiers within a communications are employed. It iscontemplated that one or more psychological behavioral models may beapplied to the voice data to generate behavioral assessment datatherefrom.

The telephonic communication 2 being analyzed can be one of numerouscalls stored within a contact center server 12, or communicated to acontact center during a given time period. Accordingly, the presentmethod contemplates that the telephonic communication 2 being subjectedto analysis is selected from the plurality of telephonic communications.The selection criteria for determining which communication should beanalyzed may vary. For example, the communications coming into a contactcenter can be automatically categorized into a plurality of call typesusing an appropriate algorithm. For example, the system may employ aword-spotting algorithm that categorizes communications 2 intoparticular types or categories based on words used in the communication.In one embodiment, each communication 2 is automatically categorized asa service call type (e.g., a caller requesting assistance for servicinga previously purchased product), a retention call type (e.g., a callerexpressing indignation, or having a significant life change event), or asales call type (e.g., a caller purchasing an item offered by a seller).In one scenario, it may be desirable to analyze all of the “sales calltype” communications received by a contact center during a predeterminedtime frame. In that case, the user would analyze each of the sales calltype communications from that time period by applying the predeterminedpsychological behavioral model to each such communication.

Alternatively, the communications 2 may be grouped according to customercategories, and the user may desire to analyze the communications 2between the call center and communicants within a particular customercategory. For example, it may be desirable for a user to perform ananalysis only of a “platinum customers” category, consisting of high endinvestors, or a “high volume distributors” category comprised of auser's best distributors.

In one embodiment the telephonic communication 2 is telephone call inwhich a telephonic signal is transmitted. As many be seen in FIGS. 7 and8, a customer sending a telephonic signal may access a contact center 10through the public switched telephone network (PSTN) 203 and anautomatic call distribution system (PBX/ACD) 205 directs thecommunication to one of a plurality of agent work stations 211, 213.Each agent work station 211, 213 includes, for example, a computer 215and a telephone 213.

When analyzing voice data, it is preferable to work from a true andclear hi-fidelity signal. This is true both in instances in which thevoice data is being translated into a text format for analysis using alinguistic-based psychological behavioral model thereto, or in instancein which a linguistic-based psychological behavioral model is beingapplied directly to an audio waveform, audio stream or file containingvoice data.

FIG. 7 illustrates a telephonic communication system 201, such as adistributed private branch exchange (PBX), having a public switchedtelephone network (PSTN) 203 connected to the PBX through a PBX switch205.

The PBX switch 205 provides an interface between the PSTN 203 and alocal network. Preferably, the interface is controlled by softwarestored on a telephony server 207 coupled to the PBX switch 205. The PBXswitch 205, using interface software, connects trunk and line stationinterfaces of the public switch telephone network 203 to stations of alocal network or other peripheral devices contemplated by one skilled inthe art. Further, in another embodiment, the PBX switch may beintegrated within telephony server 207. The stations may include varioustypes of communication devices connected to the network, including thetelephony server 207, a recording server 209, telephone stations 211,and client personal computers 213 equipped with telephone stations 215.The local network may further include fax machines and modems.

Generally, in terms of hardware architecture, the telephony server 207includes a processor, memory, and one or more input and/or output (I/O)devices (or peripherals) that are communicatively coupled via a localinterface. The processor can be any custom-made or commerciallyavailable processor, a central processing unit (CPU), an auxiliaryprocessor among several processors associated with the telephony server207, a semiconductor based microprocessor (in the form of a microchip orchip set), a macroprocessor, or generally any device for executingsoftware instructions. The memory of the telephony server 207 caninclude any one or a combination of volatile memory elements (e.g.,random access memory (RAM, such as DRAM, SRAM, SDRAM, etc.)) andnonvolatile memory elements (e.g., ROM, hard drive, tape, CDROM, etc.).The telephony server 207 may further include a keyboard and a mouse forcontrol purposes, and an attached graphic monitor for observation ofsoftware operation.

The telephony server 207 incorporates PBX control software to controlthe initiation and termination of connections between stations and viaoutside trunk connections to the PSTN 203. In addition, the software maymonitor the status of all telephone stations 211 in real-time on thenetwork and may be capable of responding to telephony events to providetraditional telephone service. This may include the control andgeneration of the conventional signaling tones such as dial tones, busytones, ring back tones, as well as the connection and termination ofmedia streams between telephones on the local network. Further, the PBXcontrol software may use a multi-port module 223 and PCs to implementstandard PBX functions such as the initiation and termination oftelephone calls, either across the network or to outside trunk lines,the ability to put calls on hold, to transfer, park and pick up calls,to conference multiple callers, and to provide caller ID information.Telephony applications such as voice mail and auto attendant may beimplemented by application software using the PBX as a network telephonyservices provider.

Referring to FIG. 9, in one embodiment, the telephony server 207 isequipped with multi-port PSTN module 223 having circuitry and softwareto implement a trunk interface 217 and a local network interface 219.The PSTN module 223 comprises a control processor 221 to manage thetransmission and reception of network messages between the PBX switch205 and the telephony network server 207. The control processor 221 isalso capable of directing network messages between the PBX switch 205,the local network interface 291, the telephony network server 207, andthe trunk interface 217. In the one embodiment, the local network usesTransmission Control Protocol/Internet Protocol (TCP/IP). The networkmessages may contain computer data, telephony transmission supervision,signaling and various media streams, such as audio data and video data.The control processor 221 directs network messages containing computerdata from the PBX switch 205 to the telephony network server 207directly through the multi-port PSTN module 223.

The control processor 221 may include buffer storage and control logicto convert media streams from one format to another, if necessary,between the trunk interface 217 and local network. The trunk interface217 provides interconnection with the trunk circuits of the PSTN 203.The local network interface 219 provides conventional software andcircuitry to enable the telephony server 207 to access the localnetwork. The buffer RAM and control logic implement efficient transferof media streams between the trunk interface 217, the telephony server207, the digital signal processor 225, and the local network interface219.

The trunk interface 217 utilizes conventional telephony trunktransmission supervision and signaling protocols required to interfacewith the outside trunk circuits from the PSTN 203. The trunk lines carryvarious types of telephony signals such as transmission supervision andsignaling, audio, fax, or modem data to provide plain old telephoneservice (POTS). In addition, the trunk lines may carry othercommunication formats such Ti, ISDN or fiber service to providetelephony or multimedia data images, video, text or audio.

The control processor 221 manages real-time telephony event handlingpertaining to the telephone trunk line interfaces, including managingthe efficient use of digital signal processor resources for thedetection of caller ID, DTMF, call progress and other conventional formsof signaling found on trunk lines. The control processor 221 alsomanages the generation of telephony tones for dialing and otherpurposes, and controls the connection state, impedance matching, andecho cancellation of individual trunk line interfaces on the multi-portPSTN module 223.

Preferably, conventional PBX signaling is utilized between trunk andstation, or station and station, such that data is translated intonetwork messages that convey information relating to real-time telephonyevents on the network, or instructions to the network adapters of thestations to generate the appropriate signals and behavior to supportnormal voice communication, or instructions to connect voice mediastreams using standard connections and signaling protocols. Networkmessages are sent from the control processor 221 to the telephony server207 to notify the PBX software in the telephony server 207 of real-timetelephony events on the attached trunk lines. Network messages arereceived from the PBX Switch 205 to implement telephone call supervisionand may control the set-up and elimination of media streams for voicetransmission.

The local network interface 219 includes conventional circuitry tointerface with the local network. The specific circuitry is dependent onthe signal protocol utilized in the local network. In one embodiment,the local network may be a local area network (LAN) utilizing IPtelephony. IP telephony integrates audio and video stream control withlegacy telephony functions and may be supported through the H.323protocol. H.323 is an International TelecommunicationUnion-Telecommunications protocol used to provide voice and videoservices over data networks. H.323 permits users to make point-to-pointaudio and video phone calls over a local area network. IP telephonysystems can be integrated with the public telephone system through alocal network interface 219, such as an IP/PBX-PSTN gateway, therebyallowing a user to place telephone calls from an enabled computer. Forexample, a call from an IP telephony client to a conventional telephonewould be routed on the LAN to the IP/PBX-PSTN gateway. The IP/PBX-PSTNgateway translates H.323 protocol to conventional telephone protocol androutes the call over the conventional telephone network to itsdestination. Conversely, an incoming call from the PSTN 203 is routed tothe IP/PBX-PSTN gateway and translates the conventional telephoneprotocol to H.323 protocol.

As noted above, PBX trunk control messages are transmitted from thetelephony server 207 to the control processor 221 of the multi-portPSTN. In contrast, network messages containing media streams of digitalrepresentations of real-time voice are transmitted between the trunkinterface 217 and local network interface 219 using the digital signalprocessor 225. The digital signal processor 225 may include bufferstorage and control logic. Preferably, the buffer storage and controllogic implement a first-in-first-out (FIFO) data buffering scheme fortransmitting digital representations of voice audio between the localnetwork to the trunk interface 217. It is noted that the digital signalprocessor 225 may be integrated with the control processor 221 on asingle microprocessor.

The digital signal processor 225 may include a coder/decoder (CODEC)connected to the control processor 221. The CODEC may be a type TCM29c13integrated circuit made by Texas Instruments, Inc. In one embodiment,the digital signal processor 225 receives an analog or digital voicesignal from a station within the network or from the trunk lines of thePSTN 203. The CODEC converts the analog voice signal into in a digitalfrom, such as digital data packets. It should be noted that the CODEC isnot used when connection is made to digital lines and devices. From theCODEC, the digital data is transmitted to the digital signal processor225 where telephone functions take place. The digital data is thenpassed to the control processor 221 which accumulates the data bytesfrom the digital signal processor 225. It is preferred that the databytes are stored in a first-in-first-out (FIFO) memory buffer untilthere is sufficient data for one data packet to be sent according to theparticular network protocol of the local network. The specific number ofbytes transmitted per data packet depends on network latencyrequirements as selected by one of ordinary skill in the art. Once adata packet is created, the data packet is sent to the appropriatedestination on the local network through the local network interface219. Among other information, the data packet contains a source address,a destination address, and audio data. The source address identifies thelocation the audio data originated from and the destination addressidentifies the location the audio data is to be sent.

The system permits bidirectional communication by implementing a returnpath allowing data from the local network, through the local networkinterface 219, to be sent to the PSTN 203 through the multi-line PSTNtrunk interface 217. Data streams from the local network are received bythe local network interface 219 and translated from the protocolutilized on the local network to the protocol utilized on the PSTN 203.The conversion of data may be performed as the inverse operation of theconversion described above relating to the IP/PBX-PSTN gateway. The datastream is restored in appropriate form suitable for transmission throughto either a connected telephone 211, 215 or an interface trunk 217 ofthe PSTN module 223, or a digital interface such as a TI line or ISDN.In addition, digital data may be converted to analog data fortransmission over the PSTN 203.

Generally, the PBX switch of the present invention may be implementedwith hardware or virtually. A hardware PBX has equipment located localto the user of the PBX system. The PBX switch 205 utilized may be astandard PBX manufactured by Avaya, Siemens AG, NEC, Nortel, Toshiba,Fujitsu, Vodavi, Mitel, Ericsson, Panasonic, or InterTel. In contrast, avirtual PBX has equipment located at a central telephone serviceprovider and delivers the PBX as a service over the PSTN 203.

As illustrated in FIG. 1, the system includes a recording server 209 forrecording and separating network messages transmitted within the system.The recording server 209 may be connected to a port on the localnetwork, as seen in FIG. 1. Alternatively, the recording server 209 maybe connected to the PSTN trunk line as illustrated in FIG. 7. Therecording server 209 includes a control system software, such asrecording software. The recording software of the invention can beimplemented in software (e.g., firmware), hardware, or a combinationthereof. In the currently contemplated best mode, the recording softwareis implemented in software, as an executable program, and is executed byone or more special or general purpose digital computer(s), such as apersonal computer (PC; IBM-compatible, Apple-compatible, or otherwise),personal digital assistant, workstation, minicomputer, or mainframecomputer. An example of a general purpose computer that can implementthe recording software of the present invention is shown in FIG. 3. Therecording software may reside in, or have portions residing in, anycomputer such as, but not limited to, a general purpose personalcomputer. Therefore, recording server 209 of FIG. 3 may berepresentative of any type of computer in which the recording softwareresides or partially resides.

Generally, hardware architecture is the same as that discussed above andshown in FIG. 3. Specifically, the recording server 209 includes aprocessor, memory, and one or more input and/or output (I/O) devices (orperipherals) that are communicatively coupled via a local interface aspreviously described. The local interface can be, for example, but notlimited to, one or more buses or other wired or wireless connections, asis known in the art. The local interface may have additional elements,which are omitted for simplicity, such as controllers, buffers (caches),drivers, repeaters, and receivers, to enable communications. Further,the local interface may include address, control, and/or dataconnections to enable appropriate communications among the othercomputer components.

As noted above, the recording server 209 incorporates recording softwarefor recording and separating a signal based on the source address and/ordestination address of the signal. The method utilized by the recordingserver 209 depends on the communication protocol utilized on thecommunication lines to which the recording server 209 is coupled. In thecommunication system contemplated by the present invention, the signalcarrying audio data of a communication between at least two users may bean analog signal or a digital signal in the form of a network message.In one embodiment, the signal is an audio data transmitted according toa signaling protocol, for example the H.323 protocol described above.

An example of a communication between an outside caller and a callcenter agent utilizing the present system 200 is illustrated in FIG. 10and described herein. In the embodiment of FIG. 10, when an outsidecaller reaches the system through the multi-line interface trunk 217,their voice signal is digitized (if needed) in the manner describedabove, and converted into digital data packets 235 according to thecommunication protocol utilized on the local network of the system. Thedata packet 235 comprises a source address identifying the address ofthe outside caller, a destination address identifying the address of thecall center agent, and first constituent audio data comprising at leasta portion of the outside caller's voice. The data packet 235 can furthercomprise routing data identifying how the data packet 235 should berouted through the system and other relevant data. Once the data packet235 is created, the data packet 235 is sent to the appropriatedestination on the local network, such as to a call center agent,through the local network interface 219. The PBX and/or an automaticcall distributor (ACD) can determine the initial communication setup,such as the connection state, impedance matching, and echo cancellation,according to predetermined criteria.

Similar to the process described above, when the call center agentspeaks, their voice is digitized (if needed) and converted into digitaldata packet 235 according to the communication protocol utilized on thelocal network. The data packet 235 comprises a source addressidentifying the address of the call center agent, a destination addressidentifying the address of the outside caller, and second constituentaudio data comprising at least a portion of the call center agent'svoice. The data packet 235 is received by the local network interface219 and translated from the communication protocol utilized on the localnetwork to the communication protocol utilized on the PSTN 203. Theconversion of data can be performed as described above. The data packet235 is restored in appropriate form suitable for transmission through toeither a connected telephone 211, 215 or an interface trunk 217 of thePSTN module 223, or a digital interface such as a Ti line or ISDN. Inaddition, digital data can be converted to analog data for transmissionthrough the PSTN 203.

The recording server 209 receives either a data packet 235 comprising:the source address identifying the address of the outside caller, adestination address identifying the address of the call center agent,and the first constituent audio data comprising at least a portion ofthe outside callers voice; or a data packet 235 comprising a sourceaddress identifying the address of the call center agent, a destinationaddress identifying the address of the outside caller, and secondconstituent audio data comprising at least a portion of the customer'sagent voice. It is understood by one of ordinary skill in the art thatthe recording server 209 is programmed to identify the communicationprotocol utilized by the local network and extract the audio data withinthe data packet 235. In one embodiment, the recording server 209 canautomatically identify the utilized communication protocol from aplurality of communication protocols. The plurality of communicationprotocols can be stored in local memory or accessed from a remotedatabase.

The recording server 209 comprises recording software to record thecommunication session between the outside caller and the call centeragent in a single data file in a stereo format. The first data file 241has at least a first audio track 237 and a second audio track 237. Oncea telephone connection is established between an outside caller and acall center agent, the recording software creates a first data file 241to record the communication between the outside caller and the callcenter agent. It is contemplated that the entire communication sessionor a portion of the communication session can be recorded.

Upon receiving the data packet 235, the recording server 209 determineswhether to record the audio data contained in the data packet 235 ineither the first audio track 237 or the second audio track 239 of thefirst data file 241 as determined by the source address, destinationaddress, and/or the audio data contained within the received data packet235. Alternatively, two first data files can be created, wherein thefirst audio track is recorded to the one of the first data file and thesecond audio track is recorded to the second first data file. In oneembodiment, if the data packet 235 comprises a source addressidentifying the address of the outside caller, a destination addressidentifying the address of the call center agent, and first constituentaudio data, the first constituent audio data is recorded on the firstaudio track 237 of the first data file 241. Similarly, if the datapacket 235 comprises a source address identifying the address of thecall center agent, a destination address identifying the address of theoutside caller, and second constituent audio data, the secondconstituent audio data is recorded on the second audio track 239 of thefirst data file 241. It should be noted the first and second constituentaudio data can be a digital or analog audio waveform or a textualtranslation of the digital or analog waveform. The recording process isrepeated until the communication link between the outside caller andcall center agent is terminated.

As noted above, the recording server 209 can be connected to the trunklines of the PSTN 203 as seen in FIG. 8. The PSTN 203 can utilize adifferent protocol and therefore, the recording server 209 is configuredto identify the communication protocol utilized by the PSTN 203,recognize the source and destination address of a signal and extract theaudio data from the PSTN 203. The recording server 209 is programmed ina manner as known to one of ordinary skill in the art.

As shown in FIG. 10, once the communication link is terminated, therecording server 209 ends the recording session and stores the singledata file having the recorded communication session in memory. After thefirst data file is stored in memory, the recording server 209 canextract either or both of the first constituent audio data from thefirst audio track of the first data file or the second constituent audiodata from the second audio track of the first data file. In oneembodiment, the first constituent audio data extracted from the firstaudio track is stored in a first constituent data file 243. Similarly,the second constituent audio data extracted from the second audio trackcan be stored in a second constituent data file 245. The first andsecond constituent data files 243, 245 can be compressed before beingstored in memory. The extracted data can be in the form of a digital oranalog audio waveform or can be a textual translation of the first orsecond constituent audio data. It is contemplated that either or both ofthe first constituent data file 243 or the second constituent data file245 can be further analyzed or processed. For example, among otherprocesses and analyses, filtering techniques can be applied to the firstconstituent data file and/or the second constituent data file. Moreover,event data, such as silence periods or over-talking, can be identifiedthrough analysis techniques known to those skilled in the art.

Further, as illustrated in FIG. 10, the first constituent data file 243and second constituent data file 245 can be merged together into asingle second data file 247. The first and second constituent data filescan be merged in a stereo format where the first constituent audio datafrom the first constituent data file 243 is stored on a first audiotrack of the second data file 247 and the second constituent audio datafrom the second constituent data file 245 is stored on a second audiotrack of the second data file 247. Alternatively, the first and secondconstituent data files can be merged in a mono format where the firstconstituent audio data from the first constituent data file 243 and thesecond constituent audio data from the second constituent data file 245are stored on a first audio track of the second data file 247.Additionally, the first and second constituent audio data can be mergedinto a document having a textual translation of the audio data. In sucha case, identifiers can be associated with each of the merged first andsecond constituent audio data in order to associate the merged firstconstituent audio data with the outside caller, and associate the mergedsecond constituent audio data with the call center agent. The seconddata file 247 can be compressed before being stored in memory.

It is known in the art that “cradle-to-grave” recording may be used torecord all information related to a particular telephone call from thetime the call enters the contact center to the later of: the callerhanging up or the agent completing the transaction. All of theinteractions during the call are recorded, including interaction with anIVR system, time spent on hold, data keyed through the caller's key pad,conversations with the agent, and screens displayed by the agent athis/her station during the transaction.

As shown in FIGS. 11-13, once the first and second constituent voicedata are separated one from the other, each of the first and secondconstituent voice data can be independently mined and analyzed. It willbe understood that “mining” as referenced herein is to be consideredpart of the process of analyzing the constituent voice data. It is alsocontemplated by the present invention that the mining and behavioralanalysis be conducted on either or both of the constituent voice data.

Even with conventional audio mining technology, application oflinguistic-based psychological behavioral models directly to an audiofile can be very difficult. In particular, disparities in dialect,phonemes, accents and inflections can impede or render burdensomeaccurate identification of words. And while it is contemplated by thepresent invention that mining and analysis in accordance with thepresent invention can be applied directly to voice data configured inaudio format, in a preferred embodiment of the present invention, thevoice data to be mined and analyzed is first translated into a textfile. It will be understood by those of skill that the translation ofaudio to text and subsequent data mining may be accomplished by systemsknown in the art. For example, the method of the present invention mayemploy software such as that sold under the brand name Audio Mining SDKby Scansoft, Inc., or any other audio mining software suitable for suchapplications.

As shown in FIGS. 11-13, the separated voice data is mined forbehavioral signifiers associated with a linguistic-based psychologicalbehavioral model. In particular, the method of the present inventionsearches for and identifies text-based keywords (i.e., behavioralsignifiers) relevant to a predetermined psychological behavioral model.

According to a one embodiment of the present invention, thepsychological behavioral model used to analyze the voice data is theProcess Communication Model™ (“PCM”) developed by Dr. Taibi Kahler. PCMis a psychological behavioral analytic tool which presupposes that allpeople fall primarily into one of six basic personality types: Reactor,Workaholic, Persister, Dreamer, Rebel and Promoter. Although each personis one of these six types, all people have parts of all six types withinthem arranged like a six-tier configuration. Each of the six typeslearns differently, is motivated differently, communicates differently,and has a different sequence of negative behaviors they engage in whenthey are in distress. Importantly, according to PCM, each personalitytype of PCM responds positively or negatively to communications thatinclude tones or messages commonly associated with another of the PCMpersonality types. Thus, an understanding of a communicant's PCMpersonality type offers guidance as to an appropriate responsive tone ormessage or wording.

According to the PCM Model the following behavioral characteristics areassociated with the respective personality types:

PROCESS COMMUNICATION MODEL (PCM) BEHAVIORAL PERSONALITY TYPECHARACTERISTICS Reactors compassionate, sensitive, and warm; great“people skills” and enjoy working with groups of people Workaholicsresponsible, logical, and organized Persisters conscientious, dedicated,and observant; tend to follow the rules and expect others to follow themDreamers reflective, imaginative, and calm Rebels creative, spontaneous,and playful Promoters resourceful, adaptable, and charming

These behavioral characteristics may be categorized by words, tones,gestures, postures and facial expressions, can be observed objectivelywith significantly high interjudge reliability. According to oneembodiment shown in FIG. 13, the present invention mines significantwords within one or both of the separated first and second constituentvoice data, and applies PCM to the identified words. For example, thefollowing behavioral signifiers (i.e., words) may be associated with thecorresponding behavioral type in the PCM Model:

PROCESS COMMUNICATION MODEL (PCM) BEHAVIORAL PERSONALITY TYPE SIGNIFIERSReactors Emotional Words Workaholics Thought Words Persisters OpinionWords Dreamers Reflection Words Rebels Reaction Words Promoters ActionWords

In another embodiment, the present method mines for such significantwords within the merged second data file 247 described above, and applyPCM to the identified words. Alternatively, the first data file 241 canbe mined for significant words. As shown in FIG. 13, when a behavioralsignifier is identified within the voice data 62, the identifiedbehavioral signifier is executed against a system database whichmaintains all of the data related to the psychological behavioral model66. Based on the behavioral signifiers identified in the analyzed voicedata, a predetermined algorithm 64 is used to decipher a linguisticpattern that corresponds to one or more of the PCM personality types 68.More specifically, the present method mines for linguistic indicators(words and phrases) that reveal the underlying personalitycharacteristics of the speaker during periods of distress.Non-linguistic indicators may also be identified to augment or confirmthe selection of a style for each segment of speech. Looking at all thespeech segments in conjunction with personality information the softwaredetermines an order of personality components for the caller by weighinga number of factors such as timing, position, quantity and interactionbetween the parties in the dialog.

In one embodiment, the behavioral assessment data 55 includes saleseffectiveness data. According to such an embodiment, the voice data ismined for linguist indicators to determine situations in which the callcenter agent made a sale or failed at an opportunity to make a sale. Thefailed opportunities may include failure to make an offer for a sale,making an offer and failure in completing the sale, or failure to make across-sale.

The resultant behavioral assessment data 55 is stored in a database sothat it may subsequently be used to comparatively analyze againstbehavioral assessment data derived from analysis of the other of thefirst and second constituent voice data 56. The software considers thespeech segment patterns of all parties in the dialog as a whole torefine the behavioral and distress assessment data of each party, makingsure that the final distress and behavioral results are consistent withpatterns that occur in human interaction. Alternatively, the rawbehavioral assessment data 55 derived from the analysis of the singlevoice data may be used to evaluate qualities of a single communicant(e.g., the customer or agent behavioral type, etc.). The resultsgenerated by analyzing voice data through application of a psychologicalbehavioral model to one or both of the first and second constituentvoice data can be graphically illustrated as discussed in further detailbelow.

It should be noted that, although one preferred embodiment of thepresent invention uses PCM as a linguistic-based psychologicalbehavioral model, it is contemplated that any known linguistic-basedpsychological behavioral model be employed without departing from thepresent invention. It is also contemplated that more than onelinguistic-based psychological behavioral model be used to analyze oneor both of the first and second constituent voice data.

In addition to the behavioral assessment of voice data, the method ofthe present invention may also employ distress analysis to voice data.As may be seen in FIG. 2, linguistic-based distress analysis ispreferably conducted on both the textual translation of the voice dataand the audio file containing voice data. Accordingly, linguistic-basedanalytic tools as well as non-linguistic analytic tools may be appliedto the audio file. For example, one of skill in the art may applyspectral analysis to the audio file voice data while applying a wordspotting analytical tool to the text file. Linguistic-based wordspotting analysis and algorithms for identifying distress can be appliedto the textual translation of the communication. Preferably, theresultant distress data is stored in a database for subsequent analysisof the communication.

As shown in FIG. 2, it is also often desirable to analyze non-linguisticphone events occurring during the course of a conversation such as holdtimes, transfers, “dead-air,” overtalk, etc. Accordingly, in oneembodiment of the present invention, phone event data resulting fromanalysis of these non-linguistic events is generated. Preferably, thephone event data is generated by analyzing non-linguistic informationfrom both the separated constituent voice data, or from the subsequentlygenerated audio file containing at least some of the remerged audio dataof the original audio waveform. It is also contemplated that the phoneevent data can be generated before the audio waveform is separated.

According to a preferred embodiment of the invention as shown in FIG.13, both the first and second constituent voice data are mined andanalyzed as discussed above 64, 66. The resulting behavioral assessmentdata 55, phone event data 70 and distress assessment data 72 from eachof the analyzed first and second constituent voice data arecomparatively analyzed in view of the parameters of the psychologicalbehavioral model to provide an assessment of a given communication. Fromthis comparative analysis, call assessment data relating to the totalityof the call may be generated 56.

Generally, call assessment data is comprised of behavioral assessmentdata, phone event data and distress assessment data. The resultant callassessment data may be subsequently viewed to provide an objectiveassessment or rating of the quality, satisfaction or appropriateness ofthe interaction between an agent and a customer. In the instance inwhich the first and second constituent voice data are comparativelyanalyzed, the call assessment data may generate resultant data usefulfor characterizing the success of the interaction between a customer andan agent.

Thus, as shown in FIGS. 11 and 12, when a computer program is employedaccording to one embodiment of the present invention, a plurality ofcode segments are provided. The program comprises a code segment forreceiving a digital electronic signal carrying an audio waveform 46. Inaccordance with the voice separation software described above, a codesegment identifies a communication protocol associated with thetelephonic signal 47. A code segment is also provided to separate firstand second constituent voice data of the communication one from theother by recording the audio waveform in stereo format to a firstelectronic data file which has a first and second audio track 48. Asdiscussed above, the first constituent voice data is automaticallyrecorded on the first audio track based on the identified communicationprotocol, and the second constituent voice data is automaticallyrecorded on the second audio track based on the identified communicationprotocol.

The software also includes a code segment for separately applying anon-linguistic based analytic tool to each of the separated first andsecond constituent voice data, and to generate phone event datacorresponding to the analyzed voice data 50. A code segment translateseach of the separated first and second constituent voice data into textformat and stores the respective translated first and second constituentvoice data in a first and second text file 52. A code segment analyzesthe first and second text files by applying a predeterminedlinguistic-based psychological behavioral model thereto 54. The codesegment generates either or both of behavioral assessment data anddistress assessment data corresponding to each of the analyzed first andsecond constituent voice data 54.

A code segment is also provided for generating call assessment data 56.The call assessment data is resultant of the comparative analysis of thebehavioral assessment data and distress assessment data corresponding tothe analyzed first voice data and the behavioral assessment data anddistress assessment data corresponding to the analyzed second voicedata. A code segment then transmits an output of event datacorresponding to at least one identifying indicia (e.g., call type, calltime, agent, customer, etc.) 58. This event data is comprised of a callassessment data corresponding to at least one identifying indicia (e.g.,a CSR name, a CSR center identifier, a customer, a customer type, a calltype, etc.) and at least one predetermined time interval. Now will bedescribed in detail the user interface for accessing and manipulatingthe event data of an analysis.

In one embodiment of the present invention shown in FIG. 13, theanalysis of the constituent voice data includes the steps of:translating constituent voice data to be analyzed into a text format 60and applying a predetermined linguistic-based psychological behavioralmodel to the translated constituent voice data. In applying thepsychological behavioral model, the translated voice data is mined 62.In this way at least one of a plurality of behavioral signifiersassociated with the psychological behavioral model is automaticallyidentified in the translated voice data. When the behavioral signifiersare identified, the behavioral signifiers are automatically associatedwith at least one of a plurality of personality types 68 associated withthe psychological behavioral model 64, 66. By applying appropriatealgorithms behavioral assessment data corresponding to the analyzedconstituent voice data is generated 55.

The method and system of the present invention is useful in improvingthe quality of customer interactions with agents and ultimately customerrelationships. In use, a customer wishing to engage in a service call, aretention call or a sales will call into (or be called by) a contactcenter. When the call enters the contact center it will be routed byappropriate means to a call center agent. As the interaction transpires,the voice data will be recorded as described herein. Eithercontemporaneously with the interaction, or after the call interactionhas concluded, the recorded voice data will be analyzed as describedherein. The results of the analysis will generate call assessment datacomprised of behavioral assessment data, distress assessment data andphone event data. This data may be subsequently used by a supervisor ortrainer to evaluate or train an agent, or take other remedial actionsuch as call back the customer, etc.

As indicated above, it is often desirable to train call center agents toimprove the quality of customer interactions with agents. Thus, as shownin FIGS. 33-36, the present invention provides a method for training thecall center agent by analyzing telephonic communications between thecall center agent and the customer. In one embodiment, a plurality ofthe pre-recorded first communications between outside callers and aspecific call center agent are identified based on an identifyingcriteria 601. The pre-recorded first communication can be one of theseparated constituent voice data or the subsequently generated audiofile containing at least some of the remerged audio waveform of theoriginal audio waveform.

The pre-recorded first communications to be used in training the callcenter agent are identified by comparatively analyzing the identifyingcriteria in view of event data 602. The event data can includebehavioral assessment data, phone event data, and/or distress assessmentdata of the communications. For example, the identifying criteria can bephone event data such as excessive hold/silence time (e.g., caller isplaced on hold for greater than predetermined time—e.g., 90 seconds—orthere is a period of silence greater than a predetermined amounttime—e.g., 30 seconds) or long duration for call type (i.e., calls thatare a predetermined percentage—e.g., 150%—over the average duration fora given call type). Additionally, the identifying criteria can bedistress assessment data such as upset customer, unresolved issue orprogram dissatisfaction or another data associated with distressassessment data. It is contemplated that the system identify potentialidentifying criteria based on an analysis of the behavioral assessmentdata, phone event data, and/or distress assessment data of thecommunications.

From this comparative analysis, coaching assessment data is generated.The coaching assessment data relates to the identified pre-recordedfirst communications corresponding to the identifying criteria 604. Forexample, if the identifying criteria is excessive hold/silence time, thecoaching assessment data includes pre-recorded first communicationshaving excessive hold/silence time. The resulting coaching assessmentdata is stored in a database so that it subsequently can be used toevaluate and/or train the call center agent to improve performance inview of the identifying criteria. Thus, if the identifying criteria wereexcessive hold/silence time, the call center agent would be trained toreduce the amount of excessive hold/silence time calls.

The coaching assessment data can further include first performance datarelated to the overall performance of the call center agent with respectto the identifying criteria. The first performance data can be derivedfrom an analysis of the identified prerecorded first communication withrespect to all communications—i.e., identified pre-recorded firstcommunication percentage (the percentage of identified pre-recordedfirst communications out of total number of communications) oridentified pre-recorded communication (total number of identifiedpre-recorded first communications). A first performance score for eachidentified pre-recorded first communication may be generated byanalyzing each identified pre-recorded first communication and thecorresponding first performance data. A composite first performancescore may be generated corresponding to the aggregate of the firstperformance scores of the plurality of identified pre-recorded firstcommunications.

The coaching assessment data can be comparatively analyzed against apredetermined criteria value threshold to evaluate the call centeragent's performance or against event data derived from a plurality ofidentified second pre-recorded communications to determine if trainingwas effective 606. As discussed above, the threshold may be apredetermined criteria set by the call center, the customer, or otherobjective or subjective criteria. Alternatively, the threshold may setby the performance score.

In order to evaluate a call center agent, the coaching assessment datais comparatively analyzed against a predetermined identifying criteriavalue threshold. In one embodiment, the first performance data relatedto the identified pre-recorded first communication is comparativelyanalyzed with the predetermined identifying criteria value threshold614. Based on the resultant comparative analysis, a notification isgenerated 616. For example, the percentage of excessive hold/silencecalls in the pre-recorded first communications is compared with theidentifying criteria value threshold. If the percentage of excessivehold/silence calls in the pre-recorded first communications is greaterthan the identifying criteria value threshold, the call center agent isunderperforming and a notification is automatically generated 616.

In one embodiment, the coaching assessment data includes saleseffectiveness data. The sales effectiveness data related to theidentified pre-recorded first communications is comparatively analyzedagainst a predetermined identifying criteria value threshold. Forexample, the percentage of calls that the call center agent failed tomake an offer for a cross-sale is compared with the identifying criteriavalue threshold. If the percentage of calls that the call center agentfailed to make an offer for a cross-sale is greater than the identifyingcriteria value threshold, the call center agent is underperforming, anda notification is generated.

In another embodiment, the first performance score for each identifiedpre-recorded first communication is compared with the second performancescore for the identifying criteria value threshold. In this case, if apredetermined number of first performance scores are less than (orgreater than) the identifying criteria value threshold, a notificationis generated. In another embodiment, the composite first performancescore for the identified pre-recorded first communications is comparedwith the second performance score for the identifying criteria valuethreshold. If the first composite performance score is less than (orgreater than) the second composite performance score, a notification isgenerated.

Preferably, the notification is an electronic communication, such as anemail transmitted to a supervisor or trainer indicating that the callcenter agent is underperforming. The notification may be any other typeof communication, such as a letter, a telephone call, or anautomatically generated message on a website. The notification permitsthe supervisor or trainer to take remedial action, such as set up atraining session for the call center agent. In one embodiment, thecoaching assessment data related to an identifying criteria can becomparatively analyzed against the identifying criteria value thresholdfor a plurality call center agents. Based on the collective comparativeanalysis, a notification is generated if a predetermined number orpercentage of call center agents are underperforming. In this manner,the trainer or supervisor is notified that multiple call center agentsneed to be trained with respect to the same criteria.

As noted above, the identifying criteria of the coaching assessment datacan also be used to train a call center agent. In order to determine ifthe call center agent training was effective, the coaching assessmentdata can be comparatively analyzed against event data derived from aplurality of identified second pre-recorded communications. To determineif the training was effective, the second pre-recorded communicationsshould have taken place after the call center agent training session.The pre-recorded second communications are identified according to thesame identifying criteria used to identify the pre-recorded firstcommunications in the coaching assessment data 608. Similar to thepre-recorded first communications, the pre-recorded secondcommunications can be one of the separated constituent voiced data orthe subsequently generated audio file containing at least some of theremerged audio waveform of the original audio waveform.

Second performance data related to the overall performance of the callcenter agent with respect to the pre-recorded second communications canbe generated. As with the first performance data, the second performancedata can be derived from an analysis of the identified pre-recordedsecond communication with respect to all communications—i.e., identifiedpre-recorded second communication percentage (the percentage ofidentified pre-recorded second communications out of total number ofcommunications) or identified pre-recorded communication (total numberof identified pre-recorded second communications). A second performancescore for each identified pre-recorded second communication may begenerated by analyzing each identified pre-recorded second communicationand the corresponding second performance data. A composite secondperformance score may be generated corresponding to the aggregate secondperformance score for each of the plurality of identified pre-recordedsecond communications.

The second performance data related to the identified pre-recordedsecond communications is comparatively analyzed with the firstperformance data of the coaching assessment data 610. Based on theresultant comparative analysis, a notification is generated 612.

In one embodiment, the identified pre-recorded second communicationpercentage is compared with the identified pre-recorded firstcommunication percentage. For example, the percentage of excessivehold/silence calls in the pre-recorded first communications that tookplace before the training session is compared with the percentage ofexcessive hold/silence calls in the pre-recorded second communicationsthat took place after the training session 610. If the percentage ofexcessive hold/silence calls in the pre-recorded second communicationsis less than the percentage of excessive hold/silence calls in thepre-recorded first communications, the training session was successful.Conversely, if the percentage of excessive hold/silence calls in thepre-recorded second communications is greater than the percentage ofexcessive hold/silence calls in the pre-recorded first communications,the training session was unsuccessful and a notification isautomatically generated 612.

In another embodiment, the first performance score for each identifiedpre-recorded first communication is compared with the second performancescore for each identified pre-recorded second communication. In thiscase, if a predetermined number of second performance scores are lessthan (or greater than) a predetermined number of first performancescores, a notification is generated. In another embodiment, thecomposite first performance score for the identified pre-recorded firstcommunications is compared with the composite second performance scorefor the identified pre-recorded second communications. If the secondcomposite performance score is less than (or greater than) the firstcomposite performance score, a notification is generated.

Preferably, the notification is an electronic communication, such as anemail transmitted to a supervisor or trainer indicating that thetraining session for the call center agent was unsuccessful. Thenotification permits the supervisor or trainer to take remedial action,such as set up another training session for the call center agent. Inone embodiment, the coaching assessment data related to an identifyingcriteria can be comparatively analyzed against event data derived from aplurality of identified second pre-recorded communications for aplurality of call center agents. Based on the collective comparativeanalysis, a notification is generated if a predetermined number orpercentage of call center agents have unsuccessful training sessions. Inthis manner, the trainer or supervisor is notified that multiple callcenter agents need to be trained with respect to the same criteria.

Graphical and pictorial analysis of the call assessment data (and eventdata) is accessible through a portal by a subsequent user (e.g., asupervisor, training instructor or monitor) through a graphical userinterface. A user of the system 1 described above interact with thesystem 1 via a unique graphical user interface (“GUI”) 400. The GUI 400enables the user to navigate through the system 1 to obtain desiredreports and information regarding the caller interaction events storedin memory. The GUI 400 can be part of a software program residing inwhole or in part in the a computer 12, or it may reside in whole or inpart on a server coupled to a computer 12 via a network connection, suchas through the Internet or a local or wide area network (LAN or WAN).Moreover, a wireless connection can be used to link to the network.

In the embodiment shown in FIGS. 14-32, the system 1 is accessed via anInternet connection from a computer. Known browser technology on thecomputer can be implemented to reach a server hosting the systemprogram. The GUI 400 for the system will appear as Internet web pages onthe display of the computer.

As shown in FIG. 14, the GUI 400 initially provides the user with aportal or “Log On” page 402 that provides fields for input of a username 404 and password 406 to gain access to the system. Additionally,the GUI 400 can direct a user to one or more pages for setting up a username and password if one does not yet exist.

Referring to FIG. 15, once logged into the system 1, the user cannavigate through the program by clicking one of the elements thatvisually appear as tabs generally on the upper portion of the displayscreen below any tool bars 408. In the embodiment shown in FIG. 15, thesystem 1 includes a PROFILES tab 410, a REVIEW tab 412, a METRICS tab414 and a COACHING tab 620. A variety of the other tabs with additionalinformation can also be made available.

The computer program associated with the present invention can beutilized to generate a large variety of reports relating to the recordedcall interaction events, the statistical analysis of each event and theanalysis of the event from the application of the psychological model.The GUI 400 is configured to facilitate a user's request for a specificreport and to visually display the reports on the user's display.

The REVIEW tab 412 enables the user to locate one or more callerinteraction events (a caller interaction event is also herein referredto as a “call”) stored in the memory. The REVIEW tab 412 includes visualdate fields or links 416, 418 for inputting a “from” and “to” daterange, respectively. Clicking on the links 416, 418 will call a pop-upcalendar for selecting a date. A drop down menu or input field forentering the desired date can also be used.

The caller interaction events are divided into folders and listed byvarious categories. The folders can be identified or be sorted by thefollowing event types: upset customer/issue unresolved; upsetcustomer/issued resolved; program dissatisfaction; long hold/silence(e.g., caller is placed on hold for greater than a predeterminedtime—e.g., 90 seconds—or there is a period of silence greater than apredetermined amount of time—e.g., 30 seconds); early hold (i.e.,customer is placed on hold within a predetermined amount of time—e.g.,30 seconds—of initiating a call); no authentication (i.e., the agentdoes not authorize or verify an account within a predeterminedtime—e.g., the first three minutes of the call); inappropriate response(e.g., the agent exhibits inappropriate language during the call);absent agent (i.e., incoming calls where the agent does not answer thecall); long duration for call type (i.e., calls that are a predeterminedpercentage over—e.g., 150%—the average duration for a given call type);and transfers (i.e., calls that end in a transfer). The categoriesinclude: customers, CSR agents, and customer service events.

The REVIEW tab 412 includes a visual link to a customer's folder 420.This includes a list of calls subdivided by customer type. The customerfolder 420 may include subfolders for corporate subsidiaries, specificpromotional programs, or event types (i.e., upset customer/issueunresolved, etc.).

The REVIEW tab 412 also includes a visual link to call center or CSRagent folders 422. This includes a list of calls divided by call centeror CSR agents. The initial breakdown is by location, followed by a listof managers, and then followed by the corresponding list of agents. TheREVIEW tab 412 also includes a visual link to a customer service folders424. This includes a list of calls subdivided by caller events, callcenter or CSR agent, and other relevant events.

The REVIEW tab 412 also includes a visual SEARCH link 426 to enable theuser to search for calls based on a user-defined criteria. This includesthe date range as discussed above. Additionally, the user can inputcertain call characteristics or identifying criteria. For example, theuser can input a specific call ID number and click the SEARCH link 426.This returns only the desired call regardless of the date of the call.The user could choose an agent from a drop down menu or list ofavailable agents. This returns all calls from the selected agent in thedate range specified. The user could also choose a caller (again from adrop down menu or list of available callers). This returns all callsfrom the selected caller(s) within the date range.

The results from the search are visually depicted as a list of calls 428as shown in FIG. 16. Clicking on any call 430 in the list 428 links theuser to a call page 432 (as shown in FIG. 17) that provides call dataand links to an audio file of the call which can be played on speakersconnected to the user's computer.

The call page 432 also includes a conversation visual field 434 fordisplaying a time-based representation of characteristics of the callbased on the psychological behavioral model. The call page 432 displaysa progress bar 436 that illustrates call events marked with event datashown as, for example, colored points and colored line segments. A key440 is provided explaining the color-coding.

The call page 432 further includes visual control elements for playingthe recorded call. These include: BACK TO CALL LIST 442; PLAY 444; PAUSE446; STOP 448; RELOAD 450; REFRESH DATA 452 and START/STOP/DURATION 454.The START/STOP/DURATION 454 reports the start, stop and duration ofdistinct call segments occurring in the call. The distinct call segmentsoccur when there is a transition from a caller led conversation to anagent led conversation—or vice versa—and/or the nature of the discussionshifts to a different topic).

The REVIEW tab 412 also provides a visual statistics link 456 fordisplaying call statistics as shown in FIG. 18. The statistics caninclude information such as call duration, average duration for calltype, caller talk time, number of holds over predetermined time periods(e.g., 90 seconds), number of silences, customer satisfaction score,etc.

The REVIEW tab 412 also provides a comments link 458. This will providea supervisor with the ability to document comments for each call thatcan be used in follow-up discussions with the appropriate agent.

The METRICS tab 414 allows the user to generate and access Reports ofcaller interaction event information. The METRICS tab 414 includes twofolders: a standard Reports folder 460 and an on-demand Reports folder.The standard reports folder 460 includes pre-defined call performancereports generated by the analytics engine for daily, weekly, monthly,quarterly, or annual time intervals. These Reports are organized aroundtwo key dimensions: caller satisfaction and agent performance. Theon-demand reports folder 462 includes pre-defined call performancereports for any time interval based around two key dimensions: callerand agent.

The GUI 400 facilitates generating summary or detailed Reports as shownin FIG. 19. The user can select a Report time range via a pop-upcalendar. For summary Reports, the user can select from: clientsatisfaction; summary by call type; and non-analyzed calls. For detailedReports, the user can indicate the type of Report requested and clickthe Open Reports link 464. Additionally, the user can generate ProgramReports. The user selects a client and filters the client by departmentsor divisions.

A CLIENT SATISFACTION REPORT 466 is shown in FIG. 20. The clientsatisfaction Report 466 is a summary level report that identifiesanalysis results by client for a specified time interval. The CLIENTSATISFACTION REPORT 466 contains a composite Satisfaction Score 468 thatranks relative call satisfaction across event filter criteria. TheCLIENT SATISFACTION REPORT 466 is also available in pre-defined timeintervals (for example, daily, weekly, monthly, quarterly, or annually).

The CLIENT SATISFACTION REPORT 466 includes a number of calls column 470(total number of calls analyzed for the associated client during thespecified reporting interval), an average duration column 472 (totalanalyzed talk time for all calls analyzed for the associated clientdivided by the total number of calls analyzed for the client), a greaterthan (“>”) 150% duration column 474 (percentage of calls for a clientthat exceed 150% of the average duration for all calls per call type), agreater than 90 second hold column 476 (percentage of calls for a clientwhere the call center agent places the client on hold for greater than90 seconds), a greater than 30 second silence column 478 (percentage ofcalls for a client where there is a period of continuous silence withina call greater than 30 seconds), a customer dissatisfaction column 480(percentage of calls for a client where the caller exhibitsdissatisfaction or distress—these calls are in the dissatisfied callerand upset caller/issue unresolved folders), a program dissatisfactioncolumn 482 (percentage of calls where the caller exhibitsdissatisfaction with the program), and a caller satisfaction column 484(a composite score that represents overall caller satisfaction for allcalls for the associated client).

The caller satisfaction column 484 is defined by a weighted percentageof the following criteria as shown in FIG. 21: >150% duration (weight20%), >90 second hold (10%), >30 second silence (10%), caller distress(20%), and program dissatisfaction (20%). All weighted values aresubtracted from a starting point of 100.

The user can generate a summary by CALL TYPE REPORT 486 as shown in FIG.22. The CALL TYPE REPORTS 486 identify analysis results by call type forthe specified interval. The summary by call type Report 486 contains acomposite satisfaction score 488 that ranks relative client satisfactionacross event filter criteria. The CALL TYPE REPORT 488 includes a calltype column 490, as well as the other columns described above.

The user can generate a NON-ANALYZED CALLS REPORT 492 as shown in FIG.23. The NON-ANALYZED CALLS REPORT 492 provides a summary level reportthat identifies non-analyzed calls for the specified time interval.

As shown in FIG. 24, the user can generate a DETAIL LEVEL REPORT 494.The detail level Report 494 identifies analysis results by client andcall type for the specified time interval. The DETAIL LEVEL REPORT 494contain a composite satisfaction score 496 that ranks relative clientsatisfaction for each call type across event filter criteria.

A PROGRAM REPORT 498 is shown in FIG. 25. This is a detail level reportthat identifies analysis results by client departments or divisions forthe specified time interval. THE PROGRAM REPORT 498 contain a compositesatisfaction score 500 that ranks relative client satisfaction for eachcall type across event filter criteria.

The user can also generate a number of CALL CENTER or CSR AGENT REPORTS.These include the following summary reports: corporate summary bylocation; CSR agent performance; and non-analyzed calls. Additionally,the user can generate team reports. The team Reports can be broken downby location, team or agent.

A CORPORATE SUMMARY BY LOCATION REPORT 502 is shown in FIG. 26. Thisdetail level Report 502 identifies analysis results by location for thespecified time interval, and contains a composite score that rankrelative client performance for each call type across event filtercriteria. The CORPORATE SUMMARY BY LOCATION REPORT 502 includes alocation column 504 (this identifies the call center location thatreceived the call), a number of calls column 506 (total number of callsreceived by the associated call center location during the specifiedreporting interval, an average duration column 508 (total analyzed talktime for all calls analyzed for the associated CSR agent divided by thetotal number of calls analyzed for the agent), a greater than 150%duration column 510 (percentage of calls for a CSR agent that exceed150% of the average duration for all calls, a greater than 90 secondhold column 512 (percentage of calls for a CSR agent where the CSRplaces the caller on hold for greater than 90 seconds), a greater than30 second silence column 514 (percentage of calls for a CSR agent wherethere is a period of continuous silence within a call greater than 30seconds), a call transfer column 516 (percentage of calls for a CSRagent that result in the caller being transferred), an inappropriateresponse column 518 (percentage of calls where the CSR agent exhibitsinappropriate behavior or language), an appropriate response column 520(percentage of calls where the CSR agent exhibits appropriate behavioror language that result in the dissipation of caller distress—thesecalls can be found in the upset caller/issue resolved folder), a noauthentication column 522 (percentage of calls where the CSR agent doesnot authenticate the caller's identity to prevent fraud), and a scorecolumn 524 (a composite score that represents overall call centerperformance for all calls in the associated call center location.)

The values 526 in the score column 524 are based on the weightedcriteria shown in FIG. 27. All weighted values are subtracted from astarting point of 100 except for “appropriate response,” which is anadditive value.

A CSR PERFORMANCE REPORT 528 is shown in FIG. 28. This is a detail levelreport that identifies analysis results by CSR for the specified timeinterval. This Report 528 contains a composite score that ranks relativeCSR performance for each call type across event filter criteria.

FIG. 29 shows a NON-ANALYZED CALLS REPORT 530. This is a detail levelreport that identifies analysis results by non-analyzed CSR calls for aspecified time interval.

A LOCATION BY TEAM REPORT 532 is shown in FIG. 30. This is a summarylevel report that identifies analysis results by location and team forthe specified time interval. This Report 532 contains a composite scorethat ranks relative CSR performance across event filter criteria byteam.

FIG. 31 shows a TEAM BY AGENT REPORT 534. This is a summary level reportthat identifies analysis results by team and agent for the specifiedtime interval. These Reports 534 contain a composite performance scorethat ranks relative CSR performance across event filter criteria byagent.

FIG. 32 shows a CSR BY CALL TYPE REPORT 536. This is detail level reportthat identifies analysis results by CSR and call type for the specifiedtime interval. These Reports 536 contain a composite performance scorethat ranks relative CSR performance across event filter criteria by calltype.

The COACHING tab 620 enables a user to locate one of more callerinteraction events to evaluate and train call center agents to improvethe quality of customer interactions with the agents. The COACHING tab620 includes visual date fields 622, 624 for inputting a “from” and “todate”, respectively. Clicking on the links 416, 418 will call a pop-upcalendar for selecting a date. A drop down menu or input field forentering the desired date can also be used.

The COACHING tab 620 displays caller interaction event information. Thecaller interaction event information includes check boxes for selectingthe caller interaction event information as the identifying criteria626. Based on the selection of the identifying criteria 626, a pluralityof pre-recorded first communications between outside caller and aspecific call center agent are identified 628. Information relating tothe identified criteria is also displayed 630. A value may be entered invisual call field 632 to specify the number of pre-identified calls todisplay.

The COACHING tab 620 includes a coaching page 634 to train the callcenter agent to improve performance in view of the identifying criteria,as illustrated in FIG. 35. The coaching page 634 displays a progress bar636 that illustrates call events marked with event data shown as, forexample, colored points and colored line segments. The coaching page 634includes a comment box 640 for the call agent to indicate areas to betrained. Comments from others may also be displayed. The coaching page634 includes a check-box 638 for requesting additional training on theselected identifying criteria.

Referring to FIG. 36, the COACHING tab 620 includes a graphicalrepresentation 642 of the number of calls that are identified based onthe identifying criteria 644. In one embodiment, the graphicalrepresentation displays the percentage of calls identified based on theidentifying criteria 644 for each week during an identified time period.In this manner, it can be determined if the training session for thecall center agent was successful.

In a still further embodiment of the present invention, a method andsystem for searching and selecting and/or navigating to specifictelephone communications is provided. Specifically, storedcommunications may be searched based on metrics, or conditions, ofinterest. For example, a user may provide search criteria to thecomputer program of the present invention, and all telephonecommunications that satisfy the search criteria may be listed anddisplayed for the user to select. Alternatively, a specific number ofcommunication that are less than the total number of communications maybe listed and displayed for selection by the user.

In one embodiment, a method for searching and selecting and/ornavigating to specific recorded communications is provided. As statedabove, communications between a customer and a contact center may bedigitized and analyzed, and assessment data is assigned to thecommunication. For example, agent performance information may beassigned to the digitized communication indicating specific informationrelating to how the contact center agent performed on the communication.Other data assigned to the communication may relate to customersatisfaction information, business process improvement information, orany other information created after analysis of the communication usingthe methods and systems provided herein.

In a first step of this embodiment, all communications, typicallytelephonic communications, may be recorded over a given time period. Forexample, the time period may be any time period, such as minutes, hours,days, etc., and assessment data may be assigned to each communicationusing the analysis systems and methods of the present invention asdescribed above. Of that set of communications that are recorded over aspecified time period, a number of communications may be culled based onhigh level criteria, in a second step of this embodiment. In a thirdstep of this embodiment, the communications may be selected based ontheir categorization according to the present invention. For example,communications based on whether they relate to “service coaching” may becut from the set of communications over the given time period. Thesecommunications may related to how the agent provided service tocustomers, such as whether the call was designated as too long, orwhether the agent was given a low agent score based on analysis of thecommunication. In addition, communications based on whether they relateto “sales coaching” may be culled from the set of communications overthe given time period. These communications may relate to whether thecommunication related to a sales opportunity.

Further, communications based on whether they related to “collectionscoaching” may be culled from the set of communications over the giventime period. These communications may relate to whether thecommunication related to a collections opportunity. In addition,communications based on “voice of the customer” may be culled from theset of communications over the given time period. These communicationsmay relate to whether the communication related to customer satisfactionor dissatisfaction. Of course, any high level criteria may beestablished and utilized to cull the set of communications from a giventime period, and the invention should not be limited as hereindescribed.

After the first cut of communications in the third step, the computerprogram may proceed under a “manual path” or an “automatic path”. If themanual path is designated or otherwise selected by a user, a graphicaluser interface (GUI) may be displayed to select conditions or metrics ofinterest in the culled communications from the given time period in afourth step. Examples of GUIs useful for the present embodiment of theinvention described herein, and further described below. In yet a fifthstep, a user may select one or more conditional metrics that may beutilized to select communications that match the one or more conditionalmetrics. For example, a user may wish to find communications based onwhether the call was inbound or outbound, whether the customer hadpreviously contacted the company before, the gender of the customer, orother criteria that may be utilized to find and display communicationshaving characteristics or assessment data matching the criteriaselected.

If the “automatic path” is selected by the user, than previouslydetermined or programmed metric conditions or criteria may be appliedagainst the communications culled from the given time period via anautomated criteria selection step.

Whether the “manual” path or the “automatic” path is chosen, thecomputer program of the present embodiment described herein may thendisplay a list of communications that meet or otherwise match with thespecified criterion or criteria designated by the user. The list may bedisplayed in the GUI, whereupon the user may then select one or more ofthe communications, and navigate to the specific communication examplesfor playback or for further analysis.

In another embodiment related to the logic, the system described hereinmay utilize “best fit” logic to search for and list communications thatmatch the specified criterion or criteria. Specifically, a method isprovided for determining the “best fit” of communications to specifiedcriteria or metrics. In a first step, a “bit map” for each communicationis constructed to specify which metric conditions or criteria are met.For example, there may be nine metric conditions or criteria utilized todetermine matches of communications. The “bit map” may simply be astring of bits or logic characters, designating whether thecommunication matches the specific metric conditions or criteriadesignated. If all nine metric conditions or criteria are met, then eachbit within the bit map may have a positive or “1” designation.Alternatively, if no metric conditions or criteria are met by thecommunication, each bit within the bit map may be designated with anegative or “0” designation. If, for example, the first six metricconditions or criteria match the communication, but the last three donot, then the bit map may have 6 positive or “1” bits followed by 3negative or “0” bits.

The bit map may then be utilized to determine the communications thatbest fit the metric conditions or criteria. Specifically, the computerprogram may then build a result set based on all calls that have theappropriate “bit map” signature. All communications in the result setmay be provided in the result set, or only those communications having acertain number of positive or “1” bits may be ordered. For example, auser may wish to only include those communications with an “all true”result (i.e., the bit map consists of all “1s” in the bit map.Alternatively, the user may decide to build a set of communicationshaving 8 “1s”.

After the computer program builds the result set, the result set is thenordered from “best to worst.” The order is provided with thecommunications having the best fit provided first and the worst fitprovided last. In the event of a bit set “tie” (where the bit set hasthe same number of positive results or 1s, each bit may be weighted sothat certain positive bits cause the communication to rank higher thanother communications with the same number of positive bits, but fordifferent metric conditions or criteria. Alternatively, communicationshaving the same number of positive bits may be ordered randomly, or bydate, or by any other condition apparent to one having ordinary skill inthe art.

The user may further designate or select a specific number of results todisplay, whereupon the list is cutoff at the specified number ofexamples. The list is then displayed to the user via the GUI. Forexample, the user may wish to have displayed only one communication thatbest matches the metric conditions or criteria applied thereto. Thecommunication having the best bit map is then displayed for the user toselect for viewing assessment data assigned thereto, for listening to orotherwise further analyzing.

In yet another embodiment, an exemplary sample GUI can illustrate a setof metric conditions or criteria that may be selected and applied tofind matching communications. In this example, a time period is selectedby inputting a date into a FROM field and a date into a TO field,thereby designating a time period. A first cut of calls has been done byuser selected high-level criteria, with the user selecting “Voice of thePeople” under calls relating to “Customer Service.” In this exemplaryGUI embodiment, the computer program has displayed on the GUI thatwithin that time period, the “agents received 1470 calls of which 29%had customer dissatisfaction” and proceeds to list user-selectablecharacteristics. Any one, some or all of these characteristics providedin the list of user-selectable characteristics may then be selected bythe user, and specified to provide metric conditions or criteria forsearching for communications that match the selected and specifiedmetric conditions or criteria. In the GUI example, one metric conditionor criterion is selected, “Had the following personalities: 25%Thoughts.” The number of calls is designated as “1” by the user, so thelist generated by the computer program and displayed on the GUI displaysonly one result, which result has the best fit for matching the selectedmetric condition or criterion. The displayed result in the listgenerated by the computer program based on the metric condition orcriterion selected by the user may then be selected for viewingassessment data assigned thereto, listening thereto, or otherwiseanalyzing the same.

While the specific embodiments have been illustrated and described,numerous modifications come to mind without significantly departing fromthe spirit of the invention, and the scope of protection is only limitedby the scope of the accompanying claims.

What is claimed is:
 1. An interface portal system, which comprises: anon-transitory computer readable medium comprising a plurality ofinstructions stored therein adapted to generate a coaching portal basedon behavioral assessment data, the plurality of instructions comprising:instructions that, when executed, analyze one or more communicationsbetween a customer and an agent, wherein the analysis comprisesinstructions that, when executed, apply a linguistic-based psychologicalbehavioral model to separated voice data for the customer, the agent, orboth, from each communication by analyzing behavioral characteristics ofthe customer, the agent, or both, based on the one or morecommunications; instructions that, when executed, identify one or morecustomer-agent interaction events based on the analyzed behavioralcharacteristics; and instructions that, when executed, display atime-based graphic representation including a plurality of theidentified customer-agent interaction events across a selected timeinterval based on one or more communications.
 2. The interface portalsystem of claim 1, which further comprises instructions that, whenexecuted, automatically generate a coaching performance score for theagent across the selected time interval.
 3. The interface portal systemof claim 1, which further comprises instructions that, when executed,automatically generate one or more coaching recommendations based on theidentified one or more customer-agent interaction events for an agent.4. The interface portal system of claim 3, which further comprisesinstructions that, when executed, deliver the one or more coachingrecommendations to the agent and compare a performance score for theagent over the selected time interval against a second performance scorefor the agent over a second selected time interval after the one or morecoaching recommendations are delivered to the agent.
 5. The interfaceportal system of claim 4, wherein the graphic representation displayedincludes a call statistics visual field selectable by a user to displaystatistics pertaining to the one or more customer-agent interactionevents.
 6. The interface portal system of claim 1, wherein the callstatistics visual field comprises one or more of: communicationduration, average communication duration by call type, customer talktime, agent talk time, customer satisfaction score, number of holds overa pre-determined time period, hold time, number of silences longer thana predetermined time period, or a combination thereof.
 7. The interfaceportal system of claim 4, which further comprises instructions that,when executed, automatically generate and deliver a notification to anagent trainer, an agent supervisor, or both.
 8. The interface portalsystem of claim 7, wherein the notification relates to a plurality ofagents regarding a need for training the plurality of agents regarding aparticular criteria.
 9. The interface portal system of claim 1, whereinthe selected time interval includes a day, a week, a month, a quarter ora year.
 10. The interface portal system of claim 1, wherein thelinguistic-based psychological behavioral model comprises a six-tierconfiguration of six basic personality types.
 11. The interface portalsystem of claim 1, wherein the communication comprises at least one of aphone call, e-mail including voice data, web interaction including voicedata, VoIP, or video including voice data.
 12. A method of providingcoaching assessment based on behavioral assessment data across one ormore recorded communications, which comprises: analyzing, by a server,one or more communications between a customer and an agent, wherein theanalysis comprises instructions that, when executed, apply alinguistic-based psychological behavioral model to separated voice datafor the customer, the agent, or both, from each communication byanalyzing behavioral characteristics of the customer, the agent, orboth, based on the one or more communications; identifying one or morecustomer-agent interaction events based on the analyzed behavioralcharacteristics; and displaying a time-based graphic representationincluding a plurality of the identified customer-agent interactionevents across a selected time interval based on one or morecommunications.
 13. The method of claim 12, which further comprisesautomatically generating a coaching performance score for the agentacross the selected time interval.
 14. The method of claim 12, whichfurther comprises automatically generating one or more coachingrecommendations based on the identified one or more customer-agentinteraction events for an agent.
 15. The method of claim 14, whichfurther comprises delivering the one or more coaching recommendations tothe agent, and comparing a performance score for the agent over theselected time interval against a second performance score for the agentover a second selected time interval after the one or more coachingrecommendations are delivered to the agent.
 16. The method of claim 12,wherein the displaying a time-based graphic representation comprisesdisplaying a call statistics visual field selectable by a user todisplay statistics pertaining to the one or more customer-agentinteraction events.
 17. The method of claim 16, wherein the callstatistics visual field is selected to comprise one or more of:communication duration, average communication duration by call type,customer talk time, agent talk time, customer satisfaction score, numberof holds over a pre-determined time period, hold time, number ofsilences longer than a predetermined time period, or a combinationthereof.
 18. The method of claim 15, which further comprisesautomatically generating and delivering a notification to an agenttrainer, an agent supervisor, or both.
 19. The method of claim 18,wherein the notification relates to a plurality of agents regarding aneed for training the plurality of agents regarding a particularcriteria.
 20. The method of claim 12, wherein the selected time intervalis a day, a week, a month, a quarter or a year.
 21. The method of claim12, wherein the linguistic-based psychological behavioral model isselected to comprise a six-tier configuration of six basic personalitytypes.
 22. The method of claim 12, wherein the communication is selectedto comprise at least one of a phone call, e-mail including voice data,web interaction including voice data, VoIP, or video including voicedata.